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From Costly Bottlenecks to Scalable Efficiency
From Costly Bottlenecks to Scalable Efficiency
CREA, a leading e-commerce solutions provider, needed to migrate from Google BigQuery to Amazon Redshift to cut costs and improve performance.
With Swarm’s AWS expertise, CREA successfully optimized its data infrastructure, unlocking cost and performance gains by 30% while ensuring scalability in 1.5 months–a record time for the client.
For an e-commerce solutions provider like CREA, data isn’t just a resource. It’s the backbone of business growth. Managing multi-channel operations, tracking customer behavior, and optimizing sales all depend on a data infrastructure that is fast, cost-efficient, and scalable.
As CREA’s operations expanded, its data warehouse built on Google BigQuery started showing limitations: Performance issues slowed down operations, and rising costs made scaling unsustainable.
CREA needed to future-proof their data infrastructure.
However, moving petabytes of data while rewriting stored procedures from BigQuery to Redshift required deep technical expertise. AWS migrations are complex, and finding the right team to execute the transition smoothly proved challenging.
Swarm introduced John Paul (JP) Alcala–Cloudbreakers' hive lead, ex-AWS Solution Architect, ex-GCash–who has a rare combination of deep AWS expertise and hands-on experience in Redshift performance tuning and dbt optimization.
JP embedded directly into CREA’s team to ensure a smooth transition:
JP managed the migration process end-to-end, enabling CREA to fully move away from BigQuery within 1.5 months, a record time for the client who has taken quarters without the right expertise for such a complex migration.
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With JP's expertise, CREA transformed its data infrastructure, unlocking cost efficiency and performance gains while ensuring a scalable, future-proof data pipeline:
CREA completed its transition from Google BigQuery to Amazon Redshift in record time.
Swarm’s optimizations delivered a 30% savings on CREA’s data warehouse costs.
Performance issues with dbt models on Redshift were resolved, with the fix shared upstream for broader impact.
